Bhattacharya, Samir K.; Singh, Nand Kishore; Kumar, Dinesh Bayesian survival analysis of clinical data using a covariate. (English) Zbl 0855.62098 REBRAPE 9, No. 2, 141-156 (1995). Summary: The Bayesian statistical analysis of clinical data on survival times arising from an exponential survival model is presented for censored samples when information on a covariate \(x\) influencing survival of patients is available. The Bayesian analysis is carried out under the assumptions of the usual squared error loss function and the gamma and the inverted gamma prior densities, respectively. Numerical illustration for clinical data on survival times of leukemia patients on the basis of a type III censored sample in presence of a covariate measurement on white blood counts is also included. The predictive density for a future observation is presented and directions for theoretical development on the basis of alternative models are briefly indicated. MSC: 62P10 Applications of statistics to biology and medical sciences; meta analysis 62F15 Bayesian inference Keywords:Bayesian posterior density; confluent hypergeometric function; gamma prior density; Gauss hypergeometric function; log-linear model; modified Bessel function; natural conjugate prior; noninformative prior quasi-density; proportional hazards model; Whittaker function; clinical data; survival times; exponential survival model; censored samples; squared error loss; inverted gamma prior densities; leukemia; covariate measurement; predictive density PDFBibTeX XMLCite \textit{S. K. Bhattacharya} et al., REBRAPE 9, No. 2, 141--156 (1995; Zbl 0855.62098)